SO-YOLOv5: Small object recognition algorithm for sea cucumber in complex seabed environment

Underwater object recognition is a prerequisite for the realization of automated seafood harvesting. To solve the problems of low recognition accuracy and poor generalization ability of existing underwater small object, this paper takes sea cucumber as research objects to research the small object r...

Full description

Saved in:

Bibliographic Details
Published in:	Fisheries research Vol. 264; p. 106710
Main Authors:	Xuan, Kui, Deng, Limiao, Xiao, Ying, Wang, Peidong, Li, Juan
Format:	Journal Article
Language:	English
Published:	Elsevier B.V 01.08.2023
Subjects:	algorithms aquaculture Aquatic animal Artificial Intelligence (AI) automation Bidirectional Feature Pyramid Network (BiFPN) Coordinate Attention (CA) data collection Deep learning Holothuroidea Object recognition Sea cucumber seafoods YOLOv5 Deep learning Sea cucumber Aquatic animal Artificial Intelligence (AI) YOLOv5 Object recognition Coordinate Attention (CA) Bidirectional Feature Pyramid Network (BiFPN)
ISSN:	0165-7836, 1872-6763
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Be the first to leave a comment!